Pose estimation.
We compare the performance of MIM and supervised pre-trained models on the COCO [1]} and CrowdPose [2]} dataset. For the COCO dataset, We train the models on the \(train2017\)  set (\(57K\)  training images) and report the performance of the COCO \(val2017\)  split (\(5K\)  images), COCO \(test\) -\(dev2017\)  split (\(20K\)  images). For the CrowdPose dataset, following the DEKR [3]}, we train the models on the CrowdPose train and val sets (\(12K\)  training images) and evaluate on the test split (\(8K\)  images). The standard average precision based on OKS is adopted as the evaluation metric for all datasets.
